5G Security Threat Landscape, AI and Blockchain

被引:3
作者
Alanazi, Mohammad N. [1 ]
机构
[1] Al Imam Mohammad Ibn Saud Islamic Univ IMSIU, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
关键词
5G; IoT; Security; Artificial intelligence; Machine learning; Blockchain; INTERNET; THINGS; CHALLENGES; SYSTEMS; IOT;
D O I
10.1007/s11277-023-10821-6
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
The convergence of Fifth Generation (5G) wireless technology and the Internet of Things (IoT) has ushered in a transformative era of enhanced connectivity and services. However, this combination has also introduced a multifaceted security landscape that necessitates a comprehensive approach to mitigate emerging threats. This paper provides an exhaustive exploration of the 5G Security Threat Landscape investigating the intricacies of security challenges while harnessing innovative solutions to protect the IoT ecosystem. The study comprehensively unravels the diversity of security requirements, including critical aspects such as authentication, encryption, network slicing, and security by design, threat detection, and collaborative frameworks. By elucidating these foundational pillars, the paper highlights the interconnection between security paradigms and technological advancements, under scoring the pivotal role played by Artificial Intelligence (AI), Machine Learning (ML), and blockchain technologies in enhancing security measures. Through an integration of interdisciplinary research, the study emphasizes the imperative of synchronizing collective efforts among stakeholders to mitigate vulnerabilities and facilitate a secure IoT environment within the dynamic 5G landscape. As the technological landscape evolves, this research contributes to the ongoing research of securing the digital infrastructures, at par with researchers, practitioners, and policymakers, as they collectively set up a secure and resilient cyberspace.
引用
收藏
页码:1467 / 1482
页数:16
相关论文
共 44 条
[1]  
Ahmad I, 2017, 2017 IEEE CONFERENCE ON STANDARDS FOR COMMUNICATIONS AND NETWORKING (CSCN), P193, DOI 10.1109/CSCN.2017.8088621
[2]   The Internet of Things: Definition, Tactile-Oriented Vision, Challenges and Future Research Directions [J].
Akinyoade, Akintayo Johnson ;
Eluwole, Opeoluwa Tosin .
THIRD INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, 2019, 797 :639-653
[3]  
[Anonymous], 2017, Malware News
[4]   Autonomic schemes for threat mitigation in Internet of Things [J].
Ashraf, Qazi Mamoon ;
Habaebi, Mohamed Hadi .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2015, 49 :112-127
[5]  
Ashton K., 2015, RFID J, V22, P97
[6]   Network Anomaly Detection: Methods, Systems and Tools [J].
Bhuyan, Monowar H. ;
Bhattacharyya, D. K. ;
Kalita, J. K. .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2014, 16 (01) :303-336
[7]   Remote timing attacks are practical [J].
Brumley, D ;
Boneh, D .
COMPUTER NETWORKS, 2005, 48 (05) :701-716
[8]   IoT Elements, Layered Architectures and Security Issues: A Comprehensive Survey [J].
Burhan, Muhammad ;
Rehman, Rana Asif ;
Khan, Bilal ;
Kim, Byung-Seo .
SENSORS, 2018, 18 (09)
[9]   A Survey of Man In The Middle Attacks [J].
Conti, Mauro ;
Dragoni, Nicola ;
Lesyk, Viktor .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2016, 18 (03) :2027-2051
[10]   Blockchain and Deep Reinforcement Learning Empowered Intelligent 5G Beyond [J].
Dai, Yueyue ;
Xu, Du ;
Maharjan, Sabita ;
Chen, Zhuang ;
He, Qian ;
Zhang, Yan .
IEEE NETWORK, 2019, 33 (03) :10-17